A noise map is generally useful in image denoising algorithms. Although some methods for noise estimation had been described in prior art, they are generally not applied to CT images. One prior art method includes even-and-odd view method that estimates the noise map for a CT image based two images respectively reconstructed from even and odd numbered views. A difference image is generated from the two reconstructed images, and a noise map is estimated from the difference image.
The even-and-odd view method possesses some interesting features. Firstly, only two sets of the views are involved in the reconstruction procedure. Namely, one set contains even numbered views while the other set contains odd numbered views. Secondly, views in the two sets are exclusive, i.e., a view is included in either one set containing even numbered views or the other set containing odd numbered views. This feature is also referred to as independent, exclusive or uncorrelated views. Thirdly, the number of views within each set is equal in the even-and-odd views approach.
The above discussed requirements for the view sets are rather limited in estimating a noise map for the CT image. It is desirable to generalize the above requirements on the view sets.